We present novel algorithms and software addressing four core problemsin computational structural biology, namely analyzing a conformationalensemble, comparing two conformational ensembles, analyzing a sampledenergy landscape, and comparing two sampled energy landscapes. Usingrecent developments in computational topology, graph theory, andcombinatorial optimization, we make two notable contributions. First,we a present a generic algorithm analyzing height fields. We then usethis algorithm to perform density based clustering of conformations,and to analyze a sampled energy landscape in terms of basins andtransitions between them. In both cases, topological persistence isused to manage ruggedness. Second, we introduce two algorithms tocompare transition graphs. The first is the classical earth mover distance metric which depends only on local minimum energyconfigurations along with their statistical weights, while the secondincorporates topological constraints inherent to conformationaltransitions.Illustrations are provided on a simplified protein model (BLN69), whosefrustrated potential energy landscape has been thoroughly studied.The software implementing our tools is also made available, and shouldprove valuable wherever conformational ensembles and energy landscapesare used.